Evidence map›Paper›PMID 42245344›Full record

ArticleFrontiers in public health2026

Multiple exposure sources and occupational fatigue profiles among healthcare workers: a cross-sectional latent profile analysis.

Lanhui Tan, Ruyi Zhang, Yifan Liao, Shi Liu, Fei Fang, Li Liu, Bilong Feng, Ying Wang

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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Lanhui Tan *Department of Nursing, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Ruyi Zhang *Department of Infectious Diseases, Zhongnan Hospital of Wuhan University, Hubei, China.
Yifan LiaoDepartment of Building Science, Tsinghua University, Beijing, China.
Shi LiuDepartment of Building Science, Tsinghua University, Beijing, China.
Fei FangJingmen Central Hospital, Jingzhou, Hubei, China.
Li LiuDepartment of Building Science, Tsinghua University, Beijing, China.
Bilong FengDepartment of Nursing, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Ying WangHubei Engineering Center for Infectious Disease Prevention, Control and Treatment, Wuhan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Occupational fatigue is a complex and widespread issue among healthcare workers, yet its heterogeneous manifestations remain inadequately studied. This study aimed to identify distinct fatigue profiles and examine the multifaceted determinants that differentiate these profiles. Methods: A cross-sectional survey was conducted among 734 healthcare workers. The assessment was conducted using the newly developed Healthcare Worker Occupational Fatigue Scale that has undergone reliability and validity tests. Latent profile analysis was used to identify occupational fatigue subgroups, and multiple logistic regression analysis was conducted to explore the influencing factors of each subgroup. Results: Latent profile analysis identified four distinguishable occupational fatigue subgroups: the compensated group (17.97%), the prodromal-symptomatic group (35.29%), the decompensated diffuse group (37.87%), and the systemic crisis group (8.86%). Multivariate logistic regression analysis revealed that perceived workload, department affiliation, number of night shifts per month, low intention to stay, noisy environment, commuting time, and individual-level factors, including gender and health status, were significant risk factors for occupational fatigue. Conclusion: Occupational fatigue among healthcare workers exhibits substantial heterogeneity and can be categorized into four distinct profiles, with multiple contributing factors. It is necessary to adopt hierarchical and personalized intervention strategies based on precise subgroup characteristics, such as systematically reducing the workload and optimizing the acoustic environment for the severe fatigue group, in order to effectively alleviate the occupational fatigue of healthcare workers.

Indexed as

FatigueHealth PersonnelOccupational DiseasesOccupational ExposureAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedRisk FactorsSurveys and QuestionnairesWorking ConditionsWorkloadexposure sourceshealthcare workerlatent profile analysisoccupational fatiguerisk factors

Identifiers

PMID42245344
PMCPMC13230211

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.